New Bounds on Optimal Sorting Networks
Abstract
We present new parallel sorting networks for $17$ to $20$ inputs. For $17, 19,$ and $20$ inputs these new networks are faster (i.e., they require less computation steps) than the previously known best networks. Therefore, we improve upon the known upper bounds for minimal depth sorting networks on $17, 19,$ and $20$ channels. Furthermore, we show that our sorting network for $17$ inputs is optimal in the sense that no sorting network using less layers exists. This solves the main open problem of [D. Bundala & J. Zavodný. Optimal sorting networks, Proc. LATA 2014].
- Publication:
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arXiv e-prints
- Pub Date:
- January 2015
- DOI:
- 10.48550/arXiv.1501.06946
- arXiv:
- arXiv:1501.06946
- Bibcode:
- 2015arXiv150106946E
- Keywords:
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- Computer Science - Discrete Mathematics;
- Computer Science - Data Structures and Algorithms
- E-Print:
- Submitted to CiE. arXiv admin note: text overlap with arXiv:1410.2736